What is Cognition AI Devin?
Devin Devin is an innovative AI software engineer developed by Cognition Labs, known for its remarkable ability to autonomously undertake complex engineering tasks. Devin Devin excels at utilizing unfamiliar technologies, creating and deploying applications, identifying and rectifying bugs in codebases, training AI models, and contributing to production repositories. One of its outstanding achievements is its performance on the SWE-bench coding benchmark, where it surpassed previous models by resolving an exceptional 13.86% of issues end-to-end. Devin Devin 's advanced long-term reasoning and planning capabilities enable it to collaborate effectively with human teammates, enhancing productivity and facilitating the pursuit of ambitious engineering goals. Cognition Labs, the creator of Devin Devin , has secured significant funding and is eager to engage with engineering projects through early access .
Who created Cognition AI Devin?
Devin, the world's first fully autonomous AI software engineer, was created by Cognition Labs. The company, led by a team with a strong background in applied AI, aims to revolutionize software engineering by introducing AI teammates like Devin. The company's exceptional team includes members with a history of notable achievements at companies such as Cursor, Scale AI, Google DeepMind, and others. Cognition Labs has received significant funding, including a $21 million Series A investment led by Founders Fund, to support the development and deployment of Devin for engineering tasks.
What is Cognition AI Devin used for?
- Long-Term Reasoning: Devin can plan and execute complex engineering tasks, adapting over time and learning from context.
- Autonomous Task Execution: Devin autonomously addresses tasks such as bug fixes, feature requests, and model training without human intervention.
- Real-Time Collaboration: Offers the ability to work alongside human engineers, reporting progress in real time and accepting feedback for joint decision-making.
- Benchmark Success: Achieves a new state of the art on the SWE-bench coding benchmark, significantly outperforming previous models in resolving coding issues.
- Using unfamiliar technologies, building and deploying apps from start to finish, autonomously finding and fixing bugs in codebases, training and fine-tuning AI models, and contributing to mature production repositories.
- Long-Term Reasoning: Planning and executing complex engineering tasks, adapting over time and learning from context
- Autonomous Task Execution: Addressing tasks like bug fixes, feature requests, and model training without human intervention
- Developer Tools Integration: Working within a sandboxed environment with a shell, code editor, and browser
- Real-Time Collaboration: Working alongside human engineers, reporting progress in real time, and accepting feedback for joint decision-making
- Benchmark Success: Achieving state-of-the-art performance on coding benchmarks, significantly outperforming previous models
- Learning unfamiliar technologies
- Building and deploying applications
- Identifying and resolving bugs
- Contributing to production codebases
- Collaborating with human teammates to enhance engineering productivity
- Autonomous Task Execution: Addressing tasks such as bug fixes, feature requests, and model training without human intervention
- Developer Tools Integration: Working within a sandboxed environment with a shell, code editor, and browser to mimic a human developer's workflow
- Benchmark Success: Achieving a new state of the art on the SWE-bench coding benchmark, significantly outperforming previous models in resolving coding issues
- Planning and executing complex engineering tasks
- Adapting over time and learning from context
- Autonomously addressing tasks like bug fixes, feature requests, and model training without human intervention
- Working alongside human engineers for real-time collaboration
- Reporting progress in real time and accepting feedback for joint decision-making
- Achieving state-of-the-art performance in resolving coding issues on the SWE-bench coding benchmark
Who is Cognition AI Devin for?
- Software engineers
- AI engineers
- Developers
- Engineering Teams
- Software Engineer
- Developer
- AI specialist
How to use Cognition AI Devin?
To use Devin, follow these steps:
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Understanding Devin: Devin is an AI software engineer designed to autonomously handle complex engineering tasks, learn new technologies, fix bugs, deploy applications, and contribute to codebases efficiently.
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Key Features of Devin:
- Long-Term Reasoning: Devin can plan and execute intricate engineering tasks, learning and adapting over time.
- Autonomous Task Execution: Devin autonomously manages bug fixes, feature requests, and model training without human intervention.
- Developer Tools Integration: Equipped with a shell, code editor, and browser, Devin works seamlessly within a sandboxed environment.
- Real-Time Collaboration: Allows real-time collaboration with human engineers, providing progress reports and accepting feedback.
- Benchmark Success: Achieves exceptional results on the SWE-bench coding benchmark, outperforming previous models significantly.
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Hiring Devin:
- Contact Cognition Labs at [email protected] to start using Devin for engineering tasks.
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About Cognition Labs: Cognition Labs is an applied AI lab focused on creating AI teammates like Devin with advanced reasoning capabilities.
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Joining Devin Early Access:
- To start using Devin, join the waitlist or contact Cognition Labs at [email protected].
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Team and Opportunities:
- Cognition Labs has a talented team with significant AI experience from top companies, and they are continually looking for new talent to join their mission.
By following these steps, you can effectively utilize Devin's advanced capabilities in software engineering tasks.
